SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL

The lower reaches of the Yajiang River are high in the east and low in the west, with abundant rainfall, and contain a large amount of hydropower resources that have not been exploited and utilized. Nonetheless, due to the unique geographical environment in southeast Tibet, rainfall debris flow is o...

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Main Authors: Y. Huang, Y. Guo, L. Su, Q. Lin
Format: Article
Language:English
Published: Copernicus Publications 2022-10-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-3-W1-2022/51/2022/isprs-annals-X-3-W1-2022-51-2022.pdf
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author Y. Huang
Y. Guo
L. Su
Q. Lin
author_facet Y. Huang
Y. Guo
L. Su
Q. Lin
author_sort Y. Huang
collection DOAJ
description The lower reaches of the Yajiang River are high in the east and low in the west, with abundant rainfall, and contain a large amount of hydropower resources that have not been exploited and utilized. Nonetheless, due to the unique geographical environment in southeast Tibet, rainfall debris flow is one of the frequent geological disasters in this area. In this research, 42 debris flow points were collected, ten disaster-causing factors were selected, and satellite elevation data were analyzed to evaluate the disaster susceptibility of the study area. The disaster-causing factors information is extracted from Arcgis. The certainty factor model (CF) was used to calculate the coefficient of certainty of 10 factors including fault distance, elevation, normalized difference vegetation index (NDVI), average annual rainfall, profile curvature, relief, silt content, TWI, SPI, and slope aspect. The Analytic Hierarchy Process (AHP), Binary Logistic Regression (LR), Random Forest (RF) and CF model were used to analyze and predict the possibility of debris flow occurrence. The results show that the accuracy of the CF-LR model is the highest under the verification of the ROC curve. In the prediction model, the high-risk areas of debris flow are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. After bringing the data of different annual rainfall into the model, it is found that the saturation critical value of debris flow water source in the study area is within the range of 600–700mm annual rainfall.
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spelling doaj.art-520ca40bc3194e45b375128e2d0e41a72022-12-22T03:54:00ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502022-10-01X-3-W1-2022515910.5194/isprs-annals-X-3-W1-2022-51-2022SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODELY. Huang0Y. Guo1L. Su2Q. Lin3Hydraulic and Civil Engineering College, Tibet Agriculture & Animal Husbandry University, Nyingchi, ChinaHydraulic and Civil Engineering College, Tibet Agriculture & Animal Husbandry University, Nyingchi, ChinaHydraulic and Civil Engineering College, Tibet Agriculture & Animal Husbandry University, Nyingchi, ChinaHydraulic and Civil Engineering College, Tibet Agriculture & Animal Husbandry University, Nyingchi, ChinaThe lower reaches of the Yajiang River are high in the east and low in the west, with abundant rainfall, and contain a large amount of hydropower resources that have not been exploited and utilized. Nonetheless, due to the unique geographical environment in southeast Tibet, rainfall debris flow is one of the frequent geological disasters in this area. In this research, 42 debris flow points were collected, ten disaster-causing factors were selected, and satellite elevation data were analyzed to evaluate the disaster susceptibility of the study area. The disaster-causing factors information is extracted from Arcgis. The certainty factor model (CF) was used to calculate the coefficient of certainty of 10 factors including fault distance, elevation, normalized difference vegetation index (NDVI), average annual rainfall, profile curvature, relief, silt content, TWI, SPI, and slope aspect. The Analytic Hierarchy Process (AHP), Binary Logistic Regression (LR), Random Forest (RF) and CF model were used to analyze and predict the possibility of debris flow occurrence. The results show that the accuracy of the CF-LR model is the highest under the verification of the ROC curve. In the prediction model, the high-risk areas of debris flow are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. After bringing the data of different annual rainfall into the model, it is found that the saturation critical value of debris flow water source in the study area is within the range of 600–700mm annual rainfall.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-3-W1-2022/51/2022/isprs-annals-X-3-W1-2022-51-2022.pdf
spellingShingle Y. Huang
Y. Guo
L. Su
Q. Lin
SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
title_full SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
title_fullStr SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
title_full_unstemmed SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
title_short SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
title_sort susceptibility assessment of rainfall induced debris flow in the lower reaches of yajiang river based on gis and cf coupling model
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-3-W1-2022/51/2022/isprs-annals-X-3-W1-2022-51-2022.pdf
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AT yguo susceptibilityassessmentofrainfallinduceddebrisflowinthelowerreachesofyajiangriverbasedongisandcfcouplingmodel
AT lsu susceptibilityassessmentofrainfallinduceddebrisflowinthelowerreachesofyajiangriverbasedongisandcfcouplingmodel
AT qlin susceptibilityassessmentofrainfallinduceddebrisflowinthelowerreachesofyajiangriverbasedongisandcfcouplingmodel